With the growth of the use of the Internet, the growth of data usage in private networks and the growth of data used by companies and other entities, both internal and external data, the need for massive data storage and massive computing power has risen. Therefore, many entities are turning to cloud computing. The terms “the cloud” or “cloud computing” may refer generally to large scale data centers that are maintained by a third party, or a company or entity, for example one that maintains systems and/or software that work with the data center(s), where the storage and computing capabilities of the numerous servers within the data center are offered to internal or external customers through one or more network connections. Because relatively small entities may have access to the large scale storage and computing power of many servers, the entities can have access to large-scale computing power that is flexible and available while lowering or eliminating the costs needed to maintain the data centers. Various databases, such as communications databases and/or databases in a cloud computing data center, may be useful for storing massive amounts of data, but in various database approaches, the data is stored in a decentralized manner, across several servers or nodes, and information regarding the relationships or correlations between the data may not be stored. In various databases, for example, communications databases and/or other forms of databases, large-scale data is formatted or structured to be most easily used for task-specific computations. In other words, data may be analyzed at the outset, for example a particular relationship may be analyzed, and then the data and the resulting conclusion are stored in a specific format. For various databases, this is called a schema. Once the initial analysis is done, it may be very time consuming and difficult to re-structure and/or re-analyze data to find a new value, short of retrieving, harvesting and/or archiving locally all the data the user is interested and then organizing and/or performing computations or routines on the data to analyze relationships.
Data has become a key asset for most modern day enterprises. Managing this data has become a major problem for the IT departments of these companies and organizations. For many years, the changes in business requirements have made it more and more difficult and expensive for enterprises to keep abreast of the changes in data—firstly, because of continuous changes in the tools and standards, and secondly because of the exponential increase in the amount of data that is being made available.
Enterprises may find it difficult to detect business value in the relationships between data points, where many different types of data exist. Trying to convert data to a heterogeneous but flexible format may likely result in incomplete information that is collected from limited points.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with the present invention as set forth in the remainder of the present application with reference to the drawings.